Research Profile
Background in mathematics, conputer science, educational psychology, and learning sciences. Training in research methods, statistics, and programming. Experience with immersive/VR learning, multimodal data, and STEM-focused learning design.
Epistemic Cognition and Emotion Regulation
Learners’ emotional experiences can lead to disciplinary engagement or abandonment. We aimed to determine how students early emotional experiences when learning during discomfort can be transmuted from liabilities into assets that promote engagement. To accomplish this aim we combine theories from Positive Psychology and Knowledge-in-Pieces. We triangulate surveys, clinical interviews, and physiological data (EDA) to determine the psychological mechanisms that underpin disciplinary engagement.
Tripartite model
Coordinate changes among subjective feelings, affect, & physiological states
Spline-based trajectories
Use natural cubic splines to model learners’ EDA curves across challenging episodes.
Bayesian patterns
Apply Bayesian models to relate EDA trajectories to shifts from discomfort to productive engagement.
Now Working on...
Grounded-Cognition Learning with a VR Lorenz Model and Eye-Tracking.
This study examines how visual attention supports learning of change in dynamical systems when graduate students explore a manipulable Lorenz model in virtual reality (VR) and then identify the matching bifurcation diagram on paper.
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